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Model Predictive Flight Control System with Full State Observer using H Method

  • Jitu SanwaleEmail author
  • Dhan Jeet Singh
Original Contribution
  • 60 Downloads

Abstract

This paper presents the application of the model predictive approach to design a flight control system (FCS) for longitudinal dynamics of a fixed wing aircraft. Longitudinal dynamics is derived for a conventional aircraft. Open loop aircraft response analysis is carried out. Simulation studies are illustrated to prove the efficacy of the proposed model predictive controller using H state observer. The estimation criterion used in the \({\text{H}}_{\infty }\) observer design is to minimize the worst possible effects of the modelling errors and additive noise on the parameter estimation.

Keywords

Flight control system H state observer Model predictive controller Receding horizon Game theory 

Notations

\({\text{A}}, {\text{B}}, {\text{C}}, {\text{D}}\)

Matrices with appropriate dimensions defining system dynamics

\({\grave{\text{A,}}} {\grave{\text{B,}}} {\grave{\text{C}}}\)

Augmented system matrices

\({\updelta }_{\text{e}} ,\;{\updelta }_{\text{t}} ,\;{\updelta }_{\text{a}} ,\;{\updelta }_{\text{r}}\)

Elevator, thrust, aileron and rudder deflections respectively, degree

\({\text{F}}_{\text{X}} , {\text{F}}_{\text{Y}} , {\text{F}}_{\text{Z}}\)

Aerodynamic forces along x, y and z axes, respectively, N

\({\text{g}}\)

Gravity, m/s2

\(\upgamma\)

Performance bound on \({\text{H}}_{\infty }\) filter/observer

\({\text{I}}_{\text{x}} , {\text{I}}_{\text{y}} , {\text{I}}_{\text{z}}\)

Mass moment of inertia about x, y and z axes, respectively, kg/m2

\({\text{I}}_{\text{xz}}\)

Product of inertia in x–z plane, kg/m2

\({\text{J}}\)

Cost function for \({\text{H}}_{\infty }\) filter/observer

\({\text{J}}_{\text{MPC}}\)

Cost function for model predictive controller

\({\text{K}}_{\text{k}}\)

\({\text{H}}_{\infty }\) filter/observer gain

\({\text{L}}, {\text{M}}, {\text{N}}\)

Aerodynamic moments about x, y and z axes, respectively, N/m

\({\text{m}}\)

Mass, kg

\({\text{p}}, {\text{q}}, {\text{r}}\)

Body axis angular rates about x, y and z axes, respectively, rad/s

\({\text{p}_{0}} ,\;{\text{S}}_{\text{k}} ,\;{\text{Q}}_{\text{k}} ,\;{\text{R}}_{\text{k}}\)

Weighting matrices

\({\upphi },\;{\uptheta },\;{\Uppsi }\)

Angles of roll, pitch and yaw, degree

\({\text{u}}_{\text{e}}\)

Forward equilibrium velocity, m/s

\({\text{u}}, {\text{v}}, {\text{w}}\)

Body axis velocities along x, y and z axes, respectively, m/s

\({\mathbb{u}}\)

Input vector

\({\mathbb{u}}_{\text{e}} , {\text{x}}_{\text{e}}\)

Equilibrium/trim input and state vectors, respectively

\({\Updelta} {\mathbb{u}}\)

Change in input vector

\({\Updelta} {\mathbb{U}}\)

Augmented input vector

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Copyright information

© The Institution of Engineers (India) 2018

Authors and Affiliations

  1. 1.Aircraft Upgrade R&D CentreHindustan Aeronautics LimitedNasikIndia

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